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February 29, 2012

In "The Pirates of Penzance," time plays a trick on Frederic, making him a victim of "a most ingenious paradox" due to his Leap Year birthday. What better way to celebrate Leap Year 2012 than to dive into books that deal with the various paradoxes and definitions of "time"? Here are a few titles to add to your reading list:

A quest to find something new by excavating the "deep time" of media's development—not by simply looking at new media's historic forerunners, but by connecting models, machines, technologies, and accidents that have until now remained separated.

A new view of the metaphysics of time, arguing that the traditional tensed-tenseless debate within analytic philosophy should be seen as the first stage in a philosophical investigation of time, and that the next stage belongs to phenomenology.

More than half a century ago, on February 28, 1953, James D. Watson and his colleague, Francis Crick, launched an age of genetic discovery with their announcement to the lunchtime patrons of the Eagle Pub in Cambridge, England, that they had “found the secret of life.” Their discovery of the structure of DNA—the most important molecule of life, which specifies the form and function of every living thing—made clear how traits are passed down through the generations. Watson and Crick’s breakthrough paved the way for an age of discovery that culminated in the announcement on June 25, 2000—not in a pub but at the White House—that the human DNA code had been determined. A few years later, Watson himself became one of the first two people to read his own personal DNA code.

After 1953, Watson went on to a celebrated career, directing a laboratory at Harvard University, then a storied scientific institution at Cold Spring Harbor on Long Island, and ultimately the Human Genome Project, which deciphered the DNA code. But shortly before his own DNA code was determined, Watson’s professional life ended amid charges of racism. He was quoted in the October 14, 2007 edition of The Sunday Times that he was “inherently gloomy about the prospect of Africa” because “all our social policies are based on the fact that their intelligence is the same as ours—whereas all the testing says not really.” He also said, “There is no firm reason to anticipate that the intellectual capacities of peoples geographically separated in their evolution should prove to have evolved identically. Our wanting to reserve equal powers of reason as some universal heritage of humanity will not be enough to make it so.”

As his comments rapidly circled the globe, drawing condemnation from his fellow scientists, the 1962 Nobel Laureate quickly apologized for them. Speaking at a meeting of the Royal Society in London on October 18, 2007, he said, “To all those who have drawn the inference from my words that Africa, as a continent, is somehow genetically inferior, I can only apologize unreservedly…That is not what I meant. More importantly, there is no scientific basis for such a belief.”...

Watson had steered into the always-dangerous shoals of the genetics of race, and he should not have been surprised that his words sank him. In our penultimate chapter we, too, venture into these treacherous waters. We will show you that there are many more genetic differences within racially defined populations such as Africans and Caucasians than between these populations. You can see the close resemblance of the DNA codes of these races if you compare the few available sequences. Or, you can wait a few years and see it when you read your entire DNA code.

The third and final Q&A for National Engineers Week 2012 is with Richard de Neufville, author (with Stefan Scholtes) of Flexibility in Engineering Design. Richard is Professor of Engineering Systems and Civil and Environmental Engineering at MIT. He was Founding Chairman of the MIT Technology and Policy Program.

What is engineering design?

To my way of thinking, engineering design is the process of creating technically sound products that provide good value for money.

Good engineering design will get the technology right--the thing will work. But that is not enough! As an early engineering educator colorfully put it, “an engineer is a person who can do for a buck what any damn fool can do for two.” Good engineering design delivers good value.

Flexibility helps deliver good value by dealing with the reality that as we cannot predict the future, we must adapt to it.

How does flexibility and engineering design relate to engineering systems?

Today, we mostly produce engineering systems--complex combinations of different kinds of engineered products.

These may be big—electrical grids serving many customers from several power plants. They may also be small—computer chips with hundreds of elements.

The modern challenge for engineers is how we design these complex assemblages of parts and capabilities. We need to deal with the network of interactions at a scale that we are not accustomed to. This is what engineering systems design is about.

Flexibility is fundamental to good engineering systems design because of the inescapable uncertainty surrounding the use and performance of engineering systems. We cannot predict exactly how these systems will function, and we cannot know how they will be used. So we need to be able to adapt to actual circumstances.

What is “forecast uncertainty”?

Simply put, we are not omniscient and cannot predict the future. We cannot be sure of what will happen. Our forecasts are thus inescapably uncertain. We need to deal with this fundamental reality.

Flexibility, the ability to adapt to the range of future conditions, is by definition an important way to deal with forecast uncertainty. If you can’t fix the future, learn to adapt and live with it.

Why are forecasts fundamental to engineering design?

Design, engineering design in particular, is about creating products for future use and enjoyment.

Picking up on the idea that good design provides good value for the money or effort expended, we want to shape and size our designs to what people will value. Good design thus implicitly relies on forecasts of what might eventually be needed or desired.

For example, good design will not create a “bridge to nowhere”. The bridge itself might be structurally and technically sound. But if it serves no purpose, it is a waste of money and not good design.

In Chapter 3, you state that “flexibility in design routinely improves performance by 25 percent or more.” Can you give an example of how design flexibility can increase a project’s value?

Design flexibility improves performance by allowing us to adapt products to future circumstances and thus to obtain good performance under a range of situations. A product without design flexibility, without the capacity to adapt, often leaves us with the wrong thing at the wrong time.

The book makes the point with the simple example of the design for a multi-story parking garage.

A standard design delivers a facility with a fixed number of levels and is likely to be too big at the beginning, and then too small when traffic builds up. However, a flexible design starts small and expands if and when needed. The flexible design thus avoids losses, and takes advantages of upside opportunities. It thus can provide a “win-win” product. Case after case show that the expected benefits from flexible design are truly significant.

What are the different kinds of flexibility for a system and how do engineers determine which flexibilities will add the most value?

An obvious kind of flexibility concerns the size of a product – can we easily expand it if needed?

For example, can we double-deck a bridge to carry more traffic, as we did for the George Washington Bridge over the Hudson River?

Another flexibility concerns capability— can we upgrade it? An example is replacing a component with a new, better version, as aircraft designers routinely do when they modernize aircraft with more powerful engines or better computers.

A different flexibility enables changes in function--can we re-purpose a product to satisfy different needs, as we do when we transform office buildings into apartment houses?

Identifying which flexibility might add the most value is a challenge! The book discusses this process. As the value of flexibility lies in the capacity to adapt to the range of futures, we first need to focus on what the range of futures might be. We then need to analyze the possible flexibilities to identify those that add the most value. The choice of flexibility thus depends on the dynamics of the context. What is right for a high-tech product may not be best for conventional construction. What is appropriate for Singapore might not be best for the United States.

Though it’s impossible to predict the future, what are the key factors that engineers should consider when designing a project or system?

The key idea is that “the forecast is ‘always wrong’”! Designers need to recognize the great likelihood of unforeseen developments that affect the performance of their products. Economic cycles alter demand, new technologies create new opportunities, and political events drive industries and markets. We need to be modest about our ability to specify requirements for a design. We thus need to recognize the great need for flexibility to adapt to future realities.

Can you describe the common obstacles that engineers face when trying to implement design flexibility?

A most common obstacle is the refrain that “flexibility is nice, but we can’t afford it”.

This mantra comes from folks who think they know exactly what is needed, and who fail to recognize the ranges of conditions for their designs. It reflects a mental block that turns a blind eye to the reality of uncertainty about needs.

What is the “Flaw of Averages”?

The “flaw of averages” is the mistake (the flaw) of believing that everything will average out (the “law” of averages). Designers make this mistake when they design products around “average” or “most likely” conditions--rather than design for the range of possible futures. When designers design around averages, they systematically estimate the value of their designs incorrectly, and make the wrong design choices.

The “flaw of averages” is a very simple and long-established mathematical fact. (It’s also called “Jensen’s law” and you can Google it for details.) Unfortunately, standard design processes fixed on a single set of requirements routinely fall into this error.

What kinds of changes (if any) do you think we need to make in engineering education?

As regards design, the most important change is for educators to open our students’ minds to the reality that forecasts of what is needed are imprecise at best. When we recognize this reality, we re-frame the design problem from meeting some fixed set of requirements to that of being able to adapt to meeting a range of requirements. The rest follows!

System Safety is a specific approach to preventing accidents that was created by aerospace engineers in the 1950s for the ICBM systems the U.S. was building then. It was an early application of system thinking to engineering, in this case, for the system property of safety. The basic concept is a “hazard” and the goal is to identify and eliminate or control hazards in order to reduce losses. This goal is accomplished through appropriate analysis, design, and management of safety-critical projects.

How did you become involved in researching System Safety?

I got involved in this topic about a week after assuming my first faculty position 30 years ago. I got a call from a system safety engineer at Hughes Aircraft Co. who wanted some help with the safety of a new torpedo system they were designing that had 15 microprocessors on it. They had no idea what to do about the software. I told him I didn’t know anything about safety or torpedos and that it sounded like a reliability problem. He replied that it was a safety problem, not a reliability problem, and that they couldn’t find anyone else that was willing to help them. I couldn’t promise much but I said I would provide the help I could. I got interested in the problem and kept working on it.

What changes are stretching the limits of engineering knowledge?

We are building systems today with a complexity level that makes it impossible for anyone to predetermine all the potential system behavior. In addition, software is becoming a major part of systems, yet traditional engineering techniques to deal with accident prevention do not apply to software. At the same time, our systems have the potential not only to harm large numbers of people and the environment, but negatively impact the lives and environment of future generations. We can no longer afford to have a few accidents and learn from them but need to prevent them before they occur.

What are some of the most important assumptions that traditional safety engineers make about the cause and prevention of accidents that you have discovered to be wrong?

Engineers assume and are taught that reliability and safety are the same thing. In complex systems, building and assuring very reliable components will have only minor impact on accidents. This incorrect assumption is based on the fact that the simpler, electro-mechanical systems of the past can be exhaustively tested and system design errors can be eliminated before the system is used. That leaves only component failures (including operator error) as the cause of accidents during use. But exhaustive testing is no longer possible in systems containing significant amounts of software. Increasingly, accidents are arising from unsafe interactions among components that have not failed (that is, they satisfy their requirements).

Engineers also assume that the old fail-safe and fault tolerant techniques, like redundancy and building in safety margins apply to the new technology, such as software, which they do not. Something different is needed.

Other important erroneous assumptions involve the role of operators in accidents and the role of assigning blame for events in preventing future accidents.

Why are safety efforts sometimes not cost-effective?

There are lots of reasons. Sometimes safety efforts are devoted simply to complying with regulations or getting the system approved by some government agency without these efforts having any impact on the actual design of the system. In other cases, the system safety engineers are doing useful things but the design engineers never get information about hazards and hazard analysis until most or all of the design has been completed. There are few if any effective and cheap ways to fix flaws in the design at that time. Additionally, the hazard analysis techniques may only look at a small part (component failures) of the causes of accidents today and may treat human error superficially. Another reason is that safety efforts may narrowly focus only on technology and not include organizational design, management, operations, and safety culture.

How can engineers work to make their safety efforts more cost-effective?

They need to apply systems thinking to engineering. How to do this is the topic of my new book. The experience on real systems so far is that the new techniques described is cheaper, easier, and more effective than what people are doing now.

What kinds of changes do you think we need in engineering education to train engineers to create safer systems?

There is almost no training in system safety today in most engineering schools. Engineers must learn on the job. A few classes exist at the graduate level but relatively few engineering students, graduate or undergraduate, are exposed to these concepts in their education. I am creating an undergraduate class in system safety at MIT which will be taught for the first time next fall. The D’Arbeloff Fund and the MIT-Singapore program are providing funding to develop the curriculum and teaching materials, which will be freely shared with anyone else who would like to teach such a class. The class is divided into four modules, which could be taught separately or integrated into other classes: (1) analyzing the causes of accidents, (2) hazard analysis, (3) design for safety, and (4) operating and managing safety-critical systems.

An engineering system is a system that has both a high degree of technical or technological complexity as well as social complexity and where both of these complexities are intertwined in a way that makes them inseparable.

It’s a system designed/evolved by humans having some purpose; it is large scale and complex and will have a management or social dimension as well as a technical one. Examples of engineering systems are the electrical grid, our road, rail and air transportation networks, and the internet. Today, most of our needs as human beings for things such as water, food, medical care, and education are being met by complex engineering systems. Many of us don’t realize how intricate the underlying systems have become when we open the water tap, take a prescribed medication, or buy food at our local grocery store.

How does engineering systems differ from “traditional” engineering?

Traditional engineering is often explained as the harnessing of mathematics and physical laws from the underlying natural sciences such as physics, chemistry, and biology to design and produce artifacts that solve useful problems and are embodied by particular technologies. Of course engineering is very much associated with these activities, but we believe that engineering has a larger role to play in society. The engineering systems described above are not simply artifacts that require technology, but they are intricate networks of hardware, software, natural elements, and human actors that interact in complex and sometimes surprising ways. One of the key aspects is that policies and regulations underline the way in which these systems are operated and evolved. Therefore, engineering must not only tackle the technological part of the design but also the social, regulatory part of system design. Rather than solving problems in different disciplinary silos, new integrated approaches are needed. Traditional engineering and the engineering systems approach are not at odds with each other—engineering systems is a broader interpretation of what engineering is and should be.

How is the language used by engineers and the language used to describe what they do changing?

The traditional engineering concepts based on physical laws such as mass, force, momentum, charge, energy, performance, stability, efficiency, etc., continue to be very important. If the products and systems produced by engineers don’t meet basic functional requirements and constraints in the end, then a viable solution has not been obtained. However, achieving technical feasibility or even optimality may no longer be enough. Increasingly, technical systems have to satisfy challenging lifecycle requirements such as being environmentally and economically sustainable, being easy to change to new circumstances, or being able to inter-operate with other systems and by a large range of human users that were not initially considered. The new language of engineers focuses increasingly on more abstract concepts such as complexity, system architecture, modularity, evolvability, regulatory compliance, policy robustness, and resilience. One of the reasons for this trend is that the world is changing at an increasingly fast pace and that, especially since 2001, we have become more aware of unintended consequences and vulnerabilities in engineering systems that are triggered by natural disasters and man-made attacks.

Can you briefly tell us about the “(re)visioning perspective” framework that you set out in the book?

The (re)visioning framework is a holistic way in which engineering systems can be viewed, models, analyzed and ultimately understood. First, we need to define the scale and scope of the system that we seek to analyze. Next, we ask what the key functions are that the system should perform, followed by mapping the relationship between the structural elements that make up the physical manifestation of the system. Finally, we want to understand how the system behaves dynamically— both at short time scales (seconds, minutes, hours, days) and at longer time scales (weeks, months, years, decades). The elements of the (re)visioning perspective challenge everyone who works on an engineering system. To understand an engineering system, and hence to improve it or address problems with it, requires a careful assessment of the system’s scale and scope, its function (or functions, since a system may have more than one), its structure (or architecture), and—because, as we would expect of a system that is partially designed and partially evolved, it is dynamic and changes over time—its temporality.

None of these can be divorced from how the system’s social complexity and social effects are understood. The interactions within these large-scale complex sociotechnical systems as well as their interactions beyond the system boundaries raise yet more challenges. Engineering systems have complex causation relationships, and analysis of complex engineering systems must rest on the foundation of bidirectional causation, considering all the feedback relationships that exist.

What are the dangers of ignoring the (re)visioning perspective?

There are a couple of things that come to mind immediately. The first is the danger of linear thinking, leading to simple extrapolation of trends into the future. Engineering systems may have very non-linear elements and feedback mechanisms leading to the potential for unexpected and non-intuitive behaviors like instabilities and failure cascades, saturation effects, or super-linear growth, as well as unexpected compensation behaviors when major failures or disruptions occur. A more fundamental danger is that the system boundary is chosen too narrow or too broad and that suggested improvements may not really work because the key levers for improvements are located elsewhere.

One of my favorite examples is the attempt to reduce congestion and pollution in Mexico City by only allowing cars with odd or even-numbered license plates to drive on any given day. Human ingenuity found many workarounds (such as purchasing a cheaper older car), ultimately undermining the intended effects of the policy.

In Chapter 4, you discuss the top “four ilities” of traditional engineering—quality, maintainability/reliability, safety, and flexibility—and state that engineering systems has made this list of “ilities” much longer. Why is that, and what would you consider to be the top four “ilities” of the engineering systems epoch?

We analyzed the prevalence of these lifecycle properties in the engineering literature going back all the way to 1884. It became clear to us that the classical engineering “illities” such as quality, safety, and reliability were essential in making artifacts such as cars, power stations, trains, and telephones work reliably and predictably. Then, during and after World War II, we detect a major shift as we entered the Epoch of Complex Systems. During the war, it was essential to produce systems effectively at a large rate; therefore, the concept of scalability and usability of weapons systems was a major factor driving success on the battlefield. Usability and the field of human factors was invented and subsequently drove major design considerations for commercial products and systems. Starting in the 1970s concern over environmental impacts and interoperability of military systems, as well as the development of the internet, gave rise to new system properties such as sustainability and interoperability, which continue to be of major interest today. Also, due to the unpredictability and rate of uncertainty in today’s world, the desire for flexibility in systems continues to increase. One of the big challenges is to develop principles, methods, and tools for designing systems to be deliberately imbued with these properties with a level of rigor and predictability that is commensurate with that of the more traditional engineering properties. It also true that system properties that were once thought to have been masters, such as safety, must now be revisited due to the increasing sociotechnical complexity of today’s systems.

What do you mean by “partially designed, partially evolved”? How does this concept apply to the MBTA?

We usually think that engineers and designers have full control over their own inventions and creations. This may be true for smaller scale artifacts like watches, toasters, and cars; however, large scale engineering systems have lifetimes of decades or centuries. Over these long time periods the underlying demographics of users, economics, political imperatives, and natural environment may change in ways that were never considered by the original designers. Thus, parts of the system may be shut down or modified and new elements may be added in time. These patterns resemble more biological evolutionary processes rather than follow the initial plan laid out by a master designer. In terms of the MBTA (Boston’s local transit system) I would like to mention the creation of the Silver Line, an innovative bus line that uses mostly dedicated lanes and tunnels and serves the airport and rapidly evolving waterfront district in South Boston. This is intimately connected to the Central Artery (“Big Dig”) project that we discuss in the book. Did the original designers of Boston’s first electric street car in 1889 envision the Silver Line? Most certainly not. The system evolved over time as new elements were added to better serve the rapidly evolving city.

What are the “enablers of success” as engineers address the engineering systems challenges that face humanity?

This is a great question. The first thing that comes to mind is humility. Engineers must become aware not only of the intended consequences of their designs but also of the unintended consequences and the larger set of forces that will promote or inhibit the adoption of new technologies or “solutions” to pressing problems. Taking a broad socio-technical perspective, while preserving or deepening our understanding of the technical and social possibilities, is essential. The (re)visioning perspective is a useful initial starting point for organizing the thinking around large scale challenges of our time. There are examples of successes in taking this perspective, such as the transformation of IBM from a manufacturer of business machines to a provider of integrated business solutions and services; the innovative approach to transportation in cities such as Curitiba, Brazil; and the progress Australia has made in managing its scarce freshwater resources.

Success depends on the barriers being broken down that today keep engineers, social scientists, and management scientists from teaming together in the most effective way to address the world’s problems. These barriers include the mental models those in various disciplines carry with them throughout their careers, the institutional obstacles that exist in academia and even in the business world, and the lack of understanding about what other disciplines might bring to the table (something we hope our book will make at least a small contribution to correcting).

Using MIT as an example, how has the focus of engineering education changed over time?

MIT has been and continues to be one of the leaders in engineering education. After the adoption of the engineering science approach after World War II (most of the big breakthroughs were led by trained physicists, not by engineers), engineering was refocused on the fundamentals of mathematics, physics, chemistry, and the other underlying natural sciences. Starting in the late 1980s and early 1990s, there was a realization that MIT needed to also directly impact industry and government practice, which led to the creation of new programs that integrated aspects of engineering with management and, to a lesser extent, with the social sciences. Degree programs such as System Design and Management (SDM), Leaders for Manufacturing (LFM)— now Leaders for Global Operations (LGO)—and the Engineering Systems Division (ESD) were driven by the need for a new and broader approach to engineering. Another example is the lifecycle-oriented curriculum known as CDIO (conceive-design-implement-operate) in Aeronautics and Astronautics, as well as the recent Gordon Engineering Leadership (GEL) program in the School of Engineering. One of the most difficult questions is how to provide a deep foundation in fundamentals while also exposing engineering students to the most important concepts (such as cost analysis, strategy, material selection, supplier sourcing, regulatory science) that often dominate engineering practice in the real world. Much work remains to be done, also at MIT.

What kinds of changes (if any) do you think we need to make in engineering education?

This may sound radical, but I think the time has come to fundamentally rethink the need for traditional departments. The distinctions between mechanical, electrical, chemical engineering , etc. are largely historical and a vestige of the past. Most of the systems and products being designed in the 21st century have a complex mix of mechanical, electrical, chemical, biological, and other cyber-physical elements and are designed for a large variety of human users. While engineers clearly must develop areas of deep expertise, it is not clear to us that this has to be done around the historically evolved stovepipes. It is interesting that none of the new universities that MIT is helping to get off the ground—such as Masdar Institute in Abu Dhabi, SUTD in Singapore, and SkTech in Moscow—have departments. They all have at their core an integrated modern curriculum that is centered on pillars or problem areas that map to large scale socio-technical challenges rather than to a set of clearly delineated governing equations such as the Navier-Stokes Equations (fluid dynamics), Maxwell's Equations (Electrical Engineering), or the Shannon-Hartley Law (Information Theory).

Engineering education must change as was also articulated in the well-known Engineer 2020 report released by the National Academy of Engineering. In the book we argue that “Engineering education, which since its early days has enjoyed a rich history, today has begun to broaden from preparing students for technical careers to educating technically grounded leaders who will run complex systems and enterprises and establish new entrepreneurial startups.” We believe that the engineering systems concepts we discuss are an important step in that direction.

February 14, 2012

The author of the classic philosophical treatment of love reflects on the trajectory, over decades, of his thoughts on love and other topics.

A vision of architecture that transcends concerns of form and function and finds the connections between the architect's wish to design a beautiful world and architecture's imperative to provide a better place for society.

A self-described failed filmmaker falls obsessively in love with her theorist-husband's colleague: a manifesto for a new kind of feminism and the power of first-person narration.

A vision of architecture that includes sculpture, machines, and technology and encapsulates the history of the human species.

February 08, 2012

A people of laughers, Langston Hughes has called his people. His poem “Laughers,” first published in Crisis in 1922 as “My People,” goes through a series of roles associated with African-Americans (singers, storytellers, dancers, but also dishwashers, cooks, and waiters), to conclude that they are laughers: “Yes, laughers…laughers…laughers— / Loud-mouthed laughers in the hands / Of Fate. “Yes, laughers…laughers…laughers” comes as a response to a doubtful question: “Laughers?” “Yes, laughers…” is the insistent answer, its insistence a function of the acknowledged irony of an African-American poet in 1922 describing his people as laughers.

“I love myself when I am laughing” is also Zora Neale Hurston’s provocative statement, an attempt to claim membership with the same people of laughers. It is a response to Carl Van Vechten, who had taken a series of photographs of her laughing; but also to Hughes and his accusations that she had put on a “happy darkie” show and played the primitive. The sentence would be the site of Hurston’s recuperation by 1970s feminism, becoming the title of her 1979 collection published by Feminist Press. It condenses an “attitude” that brought Hurston intellectual annihilation in the 1930s and posthumous fame. A list of adjectives describes the “attitude” within different contexts: quick-tempered, arrogant, rude, inconsiderate, unladylike; or, alternatively, enthusiastic, confident, unconventional, outspoken, free-minded. Photographs of Hurston laughing, marking this “attitude,” have become her trademark. One sees them wherever Hurston’s name appears. And then, “I love myself when I am laughing.” What does Hurston see when her laughter returns to her in the form of a photograph?

What is clear is that both Hughes and Hurston are deeply invested in a wider struggle over African-American laughter. Hughes would write about Hurston: “To many of her white friends, no doubt, she was a perfect ‘darkie,’ in the nice meaning they give the term—that is a naïve, childlike, sweet, humorous, and highly colored Negro.” This description came in the wake of the fight between Hughes and Hurston over the authorship of their 1930 collaborative work, Mule Bone: A Comedy of Negro Life, which they imagined would be the first African-American comedy. Their conflict is considered one of the most notorious “literary quarrels” in the history of African-American literature. “Playing the primitive” is in this context the insult one injured party throws at the other. But, in close proximity to the primivitist theme, the quarrel is also symptomatic of the desire to rescue African-American laughter from those to whom Hughes refers as Hurston’s “white friends,” known for their indulgence in fantasies of black laughter.

It would be Ralph Ellison who would take it upon himself to explicitly frame the struggle over African-American laughter, and to bridge the discussion between a wider modernism and the African-American tradition.

February 07, 2012

By coincidence, “eighteen years in the making” described each of the two books featured at the PROSE awards ceremony in Washington, DC last week. The PROSE awards recognize excellence in professional and scholarly publishing and are judged by distinguished industry experts. This year’s engaging ceremony provided, along with the chance to applaud several MIT Press category winners*, many good reminders about the things we value in scholarly publishing.

Last year’s winner of the top prize, the R.R. Hawkins Award, was Atlas of the Transatlantic Slave Trade by Eltis et al., a comprehensive reference work published by Yale University Press. At this year’s awards ceremony, we saw a new short film about the making of the Atlas. I can’t report on the details of this process, of which I have only a fuzzy grasp, but my lasting impressions from the film are the large collaborative team involved (including funders, scholars, cartographers, and the Press); and that team’s clear vision of the book form as superbly effective in presenting this material (to accompany an openly-available database). These impressions call to mind MIT Press’ Atlas of Science by Katy Börner, another Atlas that featured collaborative effort and vision behind its making.

The 2012 Hawkins award went to The Diffusion Handbook: Applied Solutions for Engineers by Thambynayagam, published by McGraw Hill.My grasp of this highly complex, 2,000-page hardcover book is even fuzzier, but I was struck by its evident usefulness for its technical audience and by the author’s invention of a new visual icon system for organizing the solutions he presents (the book contains a 125-page table of contents using these icons!).

The Diffusion Handbook reminded me of several of our own completely unique works, books whose new concepts required custom editorial solutions and/or breathtakingly detailed production work. These include Shape by George Stiny, Color for the Sciences by Jan Koenderink, Aaaaw to Zzzzzdby John Bevis, and The Book of Michael of Rhodes, volumes 1-3, edited by David McGee, Alan Stahl, and Pamela Long. Likely some of these were eighteen years (or more) in the making, as well.